Big data is shifting power over our idea of the social not just from the theorists and qualitative researchers to the data scientists, but also from academic social scientists to research labs controlled by corporations.

Wired’s Chris Anderson argued a few years ago that the social sciences are being replaced by big data and algorithmic techniques, where associations emerging from data has replaced the model of theoretical hypotheses being tested in deliberate manner by social scientists. Williamson cites such positions as "exaggerated obituaries for the social sciences,” but what is clear is that big data is challenging how and who controlled the institutional practices associated with social science “knowledge production.”

New players, often associated with corporate research labs like Facebook’s Data Science Team, are using internally generated corporate data to promote their understanding of how people behave. Studying social media is a seen as an especially rich source of behavioral data, where analyzing the use of Twitter and blogs to document everyday activities will ideally highlight massive population trends and social patterns.

However, the dark side of this shift is that such data analysis tends to focus on graphical visualization, creating in the words of researcher Lisa Gitelman a “database aesthetics” that amplifies the rhetorical function of data over more qualitative and deeper mathematical analysis as well.

As importantly, power over that knowledge has shifted increasingly to corporate R&D labs at technology companies and away from the academic researcher at universities. In fact, philosophy researcher Gary Hall sees this as a shift in the “epistemic environment” where we are abandoning the Romantic view of single authorship in favor of a corporate understanding of knowledge production.

Williamson does not emphasize this point but this shift of power over knowledge to production is also a shift from the (admittedly odd and sometimes egocentric) interests of academics to the more coldly monetary self-interest of corporate research labs in promoting data results that favor those corporation’s self interest. And since much of the data is proprietary, companies can bury results they don’t like — much as pharmaceutical companies are known to bury research results that don’t favor their prescription drug products.

Williamson outlines a social science landscape where our public discussions of how society operates will increasingly be based on results cherry-picked from corporate data sources, with other researchers often unable to challenge those results without access to the original proprietary sources.